Senior Systems Software Engineer, AV Infrastructure - Validation, Tooling, and Coverage, Senior Systems Software Engineer, AV Infrastructure - Validation, Tooling, and Coverage

NVIDIA is a leader in AI-powered applications, and they are seeking a motivated Senior Systems Software Engineer to join their Autonomous Vehicle Infrastructure organization. This role focuses on building, deploying, and operating validation platforms at scale, requiring collaboration with internal teams and external partners to enhance the validation ecosystem for autonomous driving.

Responsibilities:

• Optimize and operationalize Bazel-based build/test pipelines, integrating with CI/CD frameworks (e.g. Jenkins, GitLab)
• Enable developers with tools, wrappers, and automation using Go, Python, and Bazel that improve correctness, prevent regressions, and enforce quality gates before code is merged
• Provide mechanisms for automated analysis, triage, and reporting that helps developers and customers act on results quickly
• Deploy and operationalize vendor-provided platforms in our cloud-based service platform, starting with test environments to validate dependencies, workflows, and performance
• Provide visualization and reporting capabilities to surface validation results, coverage metrics, and actionable insights for developers and collaborators
• Communicate proactively with stakeholders, ensuring no issues are left unattended and infrastructure evolves alongside developer needs
• Partner closely with internal teams and external vendors to solve issues, refine SLAs, and continuously improve operational reliability and scalability

Requirements:

• BS/MS in Computer Science, Computer Engineering, or relevant field (or equivalent experience)
• 5+ years of professional experience in infrastructure, distributed systems, or platform engineering
• Hands-on experience with Bazel build/test automation frameworks
• Proficiency in C++, Python, and Bash coding skills
• Strong background in Linux systems, distributed systems, and infrastructure engineering
• Knowledge of cloud and on-prem environments, i.e. Kubernetes, Docker, VM infrastructure
• Strong debugging, problem-solving, and communication skills to work across internal and vendor teams
• Proven comfort leveraging AI-based development tools, such as Claude Code and Cursor
• Problem-solving mindset: capable of debugging across the stack (infra, build system, workloads)
• Prior experience with coverage frameworks (lCOV, Gcov, VectorCAST) and delivering quality metrics in compliance-heavy environments
• Hands-on experience with static analysis tooling like Coverity, and embedding it into developer workflows
• Background in safety-critical domains like automotive, with audit-driven workflows
• Experience in requirements management tools (e.g, Jama) or traceability workflows
• Strong experience in large-scale distributed systems and using AI to accelerate debug and integration workflows